Collaborative Planning of Community Charging Facilities and Distribution Networks

被引:1
|
作者
Diao, Xiao-Hong [1 ]
Zhang, Jing [1 ]
Wang, Rui-Yu [2 ]
Jia, Jiang-Wei [3 ]
Chang, Zhi-Liang [3 ]
Li, Bin [1 ]
Zhao, Xuan [1 ]
机构
[1] China Elect Power Res Inst, Battery Swap, Beijing Lab, Beijing Engn Technol Res Ctr Elect Vehicle Chargin, Beijing 100192, Peoples R China
[2] Nanyang Feilong Power Supply Serv Co Ltd, Xinye Cty Branch, Nanyang 473500, Peoples R China
[3] Tiangong Univ, Sch Elect Engn, Tianjin 300387, Peoples R China
来源
WORLD ELECTRIC VEHICLE JOURNAL | 2023年 / 14卷 / 06期
关键词
collaborative planning; charging facility; distribution network; electric vehicle; charging load forecasting; community;
D O I
10.3390/wevj14060143
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The construction of community charging facilities and supporting distribution networks based on the predicted results of electric vehicle (EV) charging power in saturation year has resulted in a large initial idleness of the distribution network and a serious waste of assets. To solve this problem, this paper proposes a collaborative planning method for urban community charging facilities and distribution networks. First, based on the load density method and occupancy rate to predict the base electricity load in the community, the Bass model and charging probability are used to predict the community's electric vehicle charging load. Taking the minimum annual construction and operation costs of the community distribution network as the objective function, the power supply topology of the distribution network for a new community is optimized by using Prim and single-parent genetic algorithms. Finally, the proposed scheme is verified by using the actual community data of a certain city in China as an analysis example, and the scheme of one-time planning of the distribution network and yearly construction of charging facilities is given.
引用
收藏
页数:19
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